Invest in the personality layer for affective AI
Personaxis turns interactions into affective memory so agents stay coherent across chat, voice, and embodied experiences. I’m raising a pre-seed round to accelerate the platform, safety tooling, and early pilots. (Solo founder, early R&D — no public product yet.)
Round snapshot
- Instrument: Pre-seed · SAFE with MFN · target $200,000 USD
- Lead / co-leads: None yet (solo founder)
- Ideal partners: affective-computing, AI infra, robotics, privacy/safety funds and strategic angels.
- Status: Planning stage — no investments closed, not publicly announced
Founder: David Q.— solo founder, CEO
Contact: davidq@personaxis.com
Use of funds
- Ship the affective memory SDK + API with governance hooks and consent ledger.
- Fund early technical hires and expand the option pool to onboard core engineers.
- Run longitudinal pilots in regulated domains (mental health, education) and robotics integrations.
- Build affective safety tooling: bias diagnostics, consent tooling, and audits.
Near-term milestones
- Jan 2026 (target): Public alpha / early version for developers — Memory Fabric MVP (multi-modal affect encoder, persona engine).
- Q2 2026: First regulated pilots — two healthcare pilots and one edtech pilot with measurable retention & safety metrics.
- Q3 2026: Platform hardening — consent ledger GA, drift sentinels and affective evaluation benchmarks.
How we work with investors
- Quarterly technical deep-dives and progress updates.
- Shared dashboards for affect accuracy, behavioral metrics and pilot KPIs.
- Scenario planning for affective deployments in sensitive domains (compliance + safety).
Send diligence requests to davidq@personaxis.com — I will provide updated metrics, data room access, and pilot references.